Reading List


Numbers and Categories

  • Hudson, P., & Ishizu, M. (2017), History by numbers. An introduction to quantitative approaches (Bloomsbury).

Additional suggested readings:

  • Lemercier, C., & Zalc, C. (2019), Quantitative Methods in the Humanities: An Introduction.

  • Graham, S., Milligan, I., Weingart, S. B., & Martin, K. (2022; 2nd edition). Exploring big historical data: the historian’s macroscope.

  • Feinstein, C.H., & Thomas, M. (2002), Making history count: A primer in quantitative methods for historians.


Texts

Topic models

  • Blei, D. M. (2012). Probabilistic topic models. Communications of the ACM 55 (4): 77–84.

  • Schmidt, B. M. (2012). Words alone: Dismantling topic models in the humanities. Journal of Digital Humanities, 2(1).

Word embedding

  • Kozlowski, A. C., Taddy, M., & Evans, J. A. (2019). The geometry of culture: Analyzing the meanings of class through word embeddings. American Sociological Review, 84(5), 905–949.

General


R Programming - Coding preparation

Additional suggested readings

These are not necessary prior to the workshop but are good reference materials for R and quantitative methods for further use.

  • Wickham, H. & Grolemund, G. (2022), R for Data Science. https://r4ds.had.co.nz

  • Imai, K., & Webb Williams, N. (2022), Quantitative Social Science: An introduction in tidyverse.

  • Hermansen, Silje S.L. (2019) Lær deg R: en innføring i statistikkprogrammets muligheter. [en fin norskspråklig innføring i R og i kvantitative metoder med gode samfunnsvitenskapelige eksempler]



2022.